Study of Cancer Radiation Therapy with Quantum Computing
Abstract
High-fidelity dose calculation is a still computationally intensive task in radiation therapy planning. While the Monte Carlo method is considered to be most accurate, its clinical application is often hindered by long computation times. Quantum computing offers a potential pathway to accelerate these simulations. We applied Quantum Monte Carlo integration (QMCI) as a proof-of-concept for radiotherapy dose calculation. Our QMCI framework consists of two main components: State preparation using quantum generative adversarial network (qGAN) and integration by applying quantum amplitude estimation (QAE) algorithm. We calculate the depth-dose distribution for a 6 MeV photon beam by focusing on the dominant firstorder Compton scattering. Our QMCI results closely reproduce the key features of the analytical and Geant4 reference depthdose curves, validating the framework’s potential as a scalable foundation for future, clinically relevant quantum applications in radiotherapy.
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